Battery Valuation and Management for Battery Swapping Station with an Intertemporal Framework
Battery swapping as a business model for battery energy storage (BES) has great potential in future integrated low-carbon energy and transportation systems. However, frequent battery swapping will inevitably accelerate battery degradation and shorten the battery life accordingly. To model the tradeoff of BES use between energy and transportation applications coupled by battery swapping, we develop a life-cycle decision model that coordinates battery charging and swapping. This model is derived based on an improved intertemporal decision framework, in which the optimal marginal degradation cost (MDC) of BES is determined to maximize the BES benefit across time and application. The proposed framework and model are applied to manage a battery swapping station that simultaneously provides battery swapping services to electric vehicle customers and provides flexibility service to the power grid, including energy arbitrage and reserve. The case study shows that while the end of the physical life of BES occurs faster with battery swapping, the economic life becomes considerably longer. The results also reveal that the optimal MDC depends on the battery values in each application, and we analyze how the battery swapping price affects the optimal MDC and battery life. The proposed framework and model can also provide decision support for on-demand BES service, such as battery trading, renting and secondary use.
Code (0)
등록된 구현이 없습니다.
Tasks
ManagementMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Facilitating Battery Swapping Services for Freight Trucks with Spatial-Temporal Demand Prediction
Electrifying heavy-duty trucks offers a substantial opportunity to curtail carbon emissions, advancing toward a carbon-neutral future. However, the inherent challenges of limited battery energy and the sheer weight of he…
PredictionElectrifying Heavy-Duty Trucks: Battery-Swapping vs Fast Charging
The advantages and disadvantages of Battery Swapping Stations (BSS) for heavy-duty trucks are poorly understood, relative to Fast Charging Stations (FCS) systems. This study evaluates these two charging mechanisms for el…
Optimal Energy Dispatch of Grid-Connected Electric Vehicle Considering Lithium Battery Electrochemical Model
The grid-connected electric vehicles (EVs) serve as a promising regulating resource in the distribution grid with Vehicle-to-Grid (V2G) facilities. In the day-ahead stage, electric vehicle batteries (EVBs) need to be pre…
Optimal scheduling of isolated microgrid with an electric vehicle battery swapping station in multi-stakeholder scenarios: a bi-level programming approach via real-time pricing
In order to coordinate the scheduling problem between an isolated microgrid (IMG) and electric vehicle battery swapping stations (BSSs) in multi-stakeholder scenarios, a new bi-level optimal scheduling model is proposed …
SchedulingTransfer Learning Assisted XgBoost For Adaptable Cyberattack Detection In Battery Packs
Optimal charging of electric vehicle (EVs) depends heavily on reliable sensor measurements from the battery pack to the cloud-controller of the smart charging station. However, an adversary could corrupt the voltage sens…
Transfer Learning